(1) Field of the Invention
The invention relates to the field of aviation. In particular, it applies to monitoring the operating and maintenance state of an aircraft, for maintenance purposes. More precisely, the invention relates to maintenance of the electronics on board an aircraft.
(2) Description of Related Art
On-board electronics is integrated in particular in avionics systems. By way of example, these may be an autopilot system, a navigation system, a health and usage monitoring system (HUMS), or indeed communications systems.
Such avionics systems comprise various pieces of on-board electronic equipment, which are referred to as line replaceable units (LRUs).
These pieces of equipment or LRUs are made up of various parts, components, or modules (e.g. an electronics card and on-board software) referred to as shop replaceable units (SRUs).
Particularly in aviation, maintenance is crucial. It involves in particular inspecting, revising, and repairing aircraft. This is essential in terms of reliability and safety.
In terms of cost, a non-negligible portion of the cost of operating an aircraft is associated with its maintenance. Maintenance also has a major influence on the operating availability of an aircraft, and thus on its profitability.
It can be understood that there is conflict between optimizing the planning of maintenance operations on an aircraft and the cost thereof. It is therefore difficult to improve the availability of an aircraft, to propose novel maintenance concepts, and also to guarantee the required level of safety.
Thus, there is conflict between the safety of making a replacement earlier than the predefined end-of-life of a component, and maximizing operating efficiency of that component by putting off maintenance for as long as possible.
The actual lifetime remaining for a given component varies depending on its operating conditions. At present, a predefined “service life” is calculated for a component, specifying a standardized length of time it can operate, expressed either as a number of operating cycles or else in units of time (typically hours).
Service life is predefined when the component is produced, and/or by standards or regulations, on the basis of empirical data, of calculated estimates, and of draconian safety margins.
The concept of a predefined “service life” should be distinguished from the concept of time to failure (TTF) which designates the effective or real maximum length of time that remains for such a component or piece of on-board electronic equipment. TTF is evaluated starting from the predefined service life. TTF is found to be satisfactory from a safety point of view, but it remains too approximate for maintenance prognosis.
Concerning time to failure, another term that is sometimes used is “remaining lifetime” or “cycles to failure” (CTF).
The predefined “service life” is identical for all components that are identical and it is predetermined. In contrast, the TTF is directly dependent on the actual number of cycles or length of operating time applicable to the component in question. It is relatively independent of the operating environment and conditions that apply thereto.
It can be understood that two components having identical predefined service lives do not necessarily have the same actual cycles or time to failure (CTF/TTF). For example, one of the components might be used under extremely difficult conditions (short lifetime), while the other is used under favorable conditions (longer lifetime).
As a result, it would appear useful to be able to have an indicator representing the tracking of the state of health and wear of pieces of equipment, expressed in terms of time to failure TTF(t), i.e. expressed in units of time.
In present practice, maintenance is thus performed only at predefined and/or regulatory time intervals, or on reaching usage values (numbers of cycles, . . . ). Maintenance also takes place in the event of a failure. This is particularly true for avionics systems, i.e. the sets of on-board electronic equipment.
As a result, the operator of an aircraft runs a risk of an unpredictable interruption of a mission. Under certain circumstances, such as aircraft for lifesaving or military missions, that is sometimes unacceptable.
To illustrate the above, we mention the 1993 specification document ARINC624-1 (in particular page 54, chapters 8.2.1 & 8.2.2) which describes research recommendations for maintaining avionics systems.
For present avionics systems that comply with the ARINC624 specification, the decision on whether or not to perform maintenance rests mainly on the results from built-in test equipment (BITE). The test provides a functional state of the LRU of the avionics system, in particular in the event of failure, with this being expressed in the form of a “NO GO” code prohibiting flight. Depending on the failure, a calculation unit may generate a functional alarm to inform the pilot.
It can be understood that in practice, it is not presently possible to have better than a binary evaluation of the instantaneous state of a piece of equipment. Either it is in working order because it is before the end of its predetermined service life, or else the equipment has reached this service life limit or has been found faulty in a test, in which case it is indicated as being not fit for use.
As a result, it is not possible at present to anticipate a failure, i.e. the moment at which it is likely to appear, nor is it possible to forecast the resources that will need to be implemented in future maintenance, nor indeed to define with sufficient certainty the future periods for which the aircraft will be available for operation. Consequently, an aircraft runs the risk of not being available for use in the event of an emergency, e.g. merely because at the time inspections were made prior to flight it was not possible to predict the failure of a piece of on-board electronic equipment that is close to the end of its TTF.
It can be seen that at present it is not common practice in aviation for maintenance concerning on-board electronic equipment to be predictive or preventative. An object of the invention is to provide predictive maintenance for on-board electronic equipment that is capable of making evaluations regularly, or even in real time, concerning the state of the various components or modules of certain pieces of on-board electronic equipment, thereby determining in real time the time they have to failure TTF(t) expressed in units of time.
Preventative or predictive maintenance in accordance with the invention would make it possible in particular to achieve two results that differ from the present state of the art, namely:
for pieces of on-board electronic equipment, it would enable failure to be forecast (as opposed to merely determining that the aircraft should be grounded “NO GO”); and
from a practical point of view, such preventative maintenance cannot be made accurate, reliable, and safe without appropriately taking into consideration the physics of failures and the classification of real measurements performed on the equipment/component under consideration.
That said, there are known predictive methods that are said to be “model” based, and other known predictive methods that are distinct therefrom and that operate by simulation, which methods are said to be “signal” based, and are applicable to fatigue, in particular.
Among the numerous model-based methods, specific tools are theoretically available that have recourse to the physics of failure.
Among the numerous signal-based methods, specific tools are available that have recourse to classifying signals, to neural networks, and to neuro-fuzzy logic.
In practice, model-based methods and signal-based methods are distinct and they are not combined. It can thus be seen that the invention brings together and combines in appropriate, novel, and meaningful manner a variety of sources of data that already exist on board or that are produced specifically and then made compatible.
At this point, mention is made of various documents relating to the field of maintenance and to evaluating damage.
Document WO 2007/085756 describes real time monitoring of the consumed lifetime of a system that may be an electronics card in the field of aviation. In operation, sensors send measurements in the form of signals that are understood by a microprocessor. Depending on the maximum acceptable movement profile and on the maximum acceptable stress profile for the system, the results of simulation are fed to a memory that contains a matrix of failure cycles.
Algorithms serve to calculate the fatigue of the system in real time. Consumed life time may be calculated on the number of life cycles or on a number of cycles to failure in order to make it possible also to integrate results obtained by finite element simulations, analytic simulations, or experimental tests.
That document also describes evaluating consumed lifetime (as a percentage and not in time units) by summing damage. This amounts to calculating a remaining lifetime indicator with a “raw” measurement that is subsequently simplified, a first stage of modeling damage to the system, and then a fairly basic second stage of estimating said lifetime.
Document XP 027218802, Lopez, describes various present techniques for monitoring structural damage to a vehicle, in particular to an airliner. In order to take into consideration impossibilities, wrong diagnoses, and inaccurate prognoses, mathematical and statistical methods are used to analyze those uncertainties on the basis of various tool boxes, including fuzzy logic, simulation measures, statistics, and probabilities.
The document (Article4_Paper_Ciri2007_Revue_JH3.pdf) from “Revue Internationale sur l'Ingénierie des Risques Industriels” [International Review on Industrial Risk Engineering], Vol. 1, No. 2 (2008), entitled “Crédit de maintenance, de la surveillance des pièces méchaniques d'un aéronef de la maintenance dynamique” [Maintenance credit, from monitoring mechanical parts of an aircraft to dynamic maintenance] mentions in Chapter 3.3 a “maintenance credit function”, the notion of “accumulated damage” and “updating calculation of time before overhaul (TBO)”, and the fact that indicators calculated during the first phase of treatment of the raw data are used as input to certain calculation models and has recourse to fuzzy logic, also known as “fusion”.
The document (Pentom07_Samir.pdf) “PENTOM 2005” entitled “Maintenance prédictive appliquée aux systèmes électroniques embarqués” [Predictive maintenance applied to on-board electronic systems] draws a distinction between two approaches that are distinct and separate in order to implement the predictive maintenance function, namely an exclusively “model-based” approach or an exclusively “signal-based” approach, which approaches do not make use of the same models and require different capture means. Mention may be made of: http://hal.archives-ouvertes.fr/docs00/18/54/97/PDF/Pento m07 Samir.pdf
Document CA 2 055 566 describes an automated helicopter maintenance monitoring system. Data is collected from a plurality of sensors, representative of vibration, rotor blade balancing, rotor phase, and mode of flight. This data is used to define when helicopter failure has occurred or is going to occur. The object is to limit excessive vibration without involving an excessive number of test hours, in particular in order to avoid cracking in a planet gear support on a UH-60A aircraft. Software implements various kinds of processing on the basis of the captured data and predefined fatigue thresholds.
Document EP 0 407 179 describes systems for monitoring the use and the operating state of a helicopter, without making provision for real-time analysis of the risks of on-board electronics equipment failing.
Document EP 1 455 313 describes an aircraft condition analysis management system (ACAMS) (ARINC). Physical parameters (temperature, vibration, etc.) are used, together with flight parameters, performance parameters, and autotest data for the purpose of monitoring mechanical or structural components of the aircraft.
Document FR 2 676 556 describes providing maintenance assistance for an industrial process, using two processors in which the more complex second processor is guided by information produced by the first processor in order to select a monitoring plan as a function of the state of said industrial process.
Document FR 2 778 766 describes providing maintenance assistance for a helicopter. Maintenance information is selectively delivered to a monitoring and pilot-viewing system.
Document FR 2 841 352 describes displaying maintenance data on a screen for viewing by the pilot of a helicopter, which data is listed and accessible from outside the helicopter via interfaces.
Document U.S. Pat. No. 5,719,675 describes predicting the remaining lifetime of a navigation laser gyro as a function of acquired performance parameters.
Documents U.S. Pat. No. 6,941,204 and U.S. Pat. No. 7,050,894 describe airliner diagnosis for the purpose of facilitating repairs, with a receiver for bringing up to the airplane on the ground so as to enable it to transmit maintenance-assistance information without making contact.
Document U.S. Pat. No. 7,474,989 describes predicting failures of an electronic assembly on the basis of lifetime consumption and environment monitoring. Environment sensors (in situ sensors) are coupled from a logical point of view to a sacrificial sensor. Values for temperature, vibration, corrosion, humidity, impedance, and voltage are measured for this purpose. Correlation and a correction loop are provided in order to form a prediction message.
Document US 2002/0107589 describes determining parameters that describe changes within a technical system as a result of aging. Performance quantities that depend on the use of the technical system are applied to a model of wear and tear so as to derive therefrom a remaining lifetime in terms of service.
Document WO 02/18879 describes predicting a remaining service life on the basis of signals from detectors (electrical current, voltage, capacitance, inductance). Detection takes place in real time and may be applied to maintenance, for various structures including an electronic device, e.g. for use in an aircraft.
Document WO 2007/008940 describes intelligent diagnosis of fault monitoring for predictive maintenance. An analysis layer makes use of numerous layered treatments including threshold rules, neural networks, Fourier transforms, etc., and also dynamic models.
Document WO 2007/085756 describes monitoring an environmental magnitude in real time on the basis of signals from measurement sensors that are subsequently filtered.
From the above, it can be understood that in spite of a large amount of research, prognosis is not available in practice in aviation for use with on-board electronic equipment and capable of taking advantage of a combination of methods (modeling plus simulation, analysis of signals (both from simulation and from operation), and then fusing compatible data), making use of common resources and implementing a novel and inventive classification of the indicators as produced in this way so as to be capable, in real time, of providing a reliable estimate of the remaining lifetime (given in units of time, e.g. hours, minutes, or seconds) for said equipment.